Autodesk
Technology
PrincipalEngineer–DataPlatform&Backend
Neural analysis suggests this role is
optimal for Senior candidates.
“Principal Engineer– Data Platform & Backend at Autodesk. Skills: Data Platform Engineering, Backend Engineering, Data Architecture, Data Pipelines. Lead architecture and implementation of data platforms. Lead architecture and implementation of data pipelines”
Industry & Context.
Pragmatic architecture decisions
What They're Looking For.
Must Have
10+ years engineering experience, 3+ years technical leadership, Proven large-scale data platforms experience, SQL expertise, Python expertise, Data modeling expertise, Distributed systems expertise, Cloud data architecture expertise, Modern data platforms experience, Batch and streaming technologies experience, Orchestration and transformation tools experience, Backend engineering experience, APIs experience, Microservices experience, Event-driven architecture experience, Service-to-data platform integrations experience, Cloud platforms experience, Data quality understanding, Data governance understanding, Data lineage understanding, Data observability understanding, Schema evolution understanding, CI/CD understanding, Production operations understanding, Pragmatic architecture decisions ability, Bachelor's degree in Computer Science
What You'll Do.
Lead architecture and implementation of data platforms
Lead architecture and implementation of data pipelines
Lead architecture and implementation of data products
Design and build batch processing systems
Design and build real-time processing systems
Design and build event-driven processing systems
Own data architecture patterns
Build reliable data ingestion layers
Build reliable data transformation layers
Build reliable data orchestration layers
Build reliable data serving layers
Design data-intensive backend services
Expose trusted data to products
Expose trusted data to platforms
Expose trusted data to consumers
Define standards for ETL/ELT
Define standards for streaming
Define standards for data validation
Define standards for observability
Define standards for monitoring
Define standards for metadata management
Define standards for pipeline reliability
Work with cloud platforms
Work with data platforms
Partner with Engineering teams
Partner with Product teams
Partner with Data Science teams
Partner with Analytics teams
Partner with DevOps teams
Partner with Security teams
Partner with FinOps teams
Translate business needs into data solutions
Translate platform needs into data solutions
Optimize data systems for performance
Optimize data systems for reliability
Optimize data systems for cost
Optimize data systems for security
Optimize data systems for operational excellence
Contribute to technical roadmap planning
Contribute to platform modernization
Contribute to technical debt reduction
Contribute to adoption of modern data architecture patterns
Raise engineering bar across data design
Raise engineering bar across data implementation
Raise engineering bar across data testing
Raise engineering bar across data observability
Raise engineering bar across data operations
Raise engineering bar across data ownership
How You'll Work.
Team & Collaboration
Across multiple teams; Partner with Engineering; Partner with Product; Partner with Data Science; Partner with Analytics; Partner with DevOps; Partner with Security; Partner with FinOps
Process & Methodology
Roadmap planning
Full Job Description
**Job Requisition ID #** 26WD96752 **Position Overview** Autodesk is a global leader in 3D design, engineering, and entertainment software, empowering innovators to design and make a better world. Our platforms support millions of users across industries including architecture, engineering, construction, manufacturing, and media. The Growth Experience Technology (GET) organization is seeking a Principal Engineer– Data Platform & Backend to lead the evolution of scalable data platforms, data pipelines, and data-intensive backend services powering digital experience, commerce, and customer intelligence platforms. This is primarily a data platform engineering hands-on leadership role, with backend engineering as an important enabling capability. The ideal candidate will own modern data architecture, batch and streaming pipelines, data models, data quality, governance, and cloud- scale data systems, while also designing APIs, services, and integrations that make trusted data accessible, reliable, and product-ready. This is a high-impact technical hands-on leadership role responsible for defining architecture, scaling data platforms, and enabling AI-driven personalization, experimentation, customer intelligence, and decision intelligence at global scale. You will operate across multiple teams as a technical authority, mentor, and strategic driver, shaping both execution and long-term technical vision. **Roles & Responsibilities** * Lead the architecture and implementation of scalable enterprise data platforms, data * pipelines, and data products. * Design and build batch, real-time, and event-driven data processing systems. * Own data architecture patterns including data modeling, lakehouse design, data * contracts, schema evolution, lineage, quality, and governance. * Build reliable data ingestion, transformation, orchestration, and serving layers for digital experience, commerce, customer intelligence, analytics, operational reporting, and AI/ML readiness. * Design dat
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